Abstract
The multi-objective firm expansion problem on competitive facility location model, and an evolutionary algorithm suitable to solve multi-objective optimization problems are reviewed in the paper. Several strategies to parallelize the algorithm utilizing both the distributed and shared memory parallel programing models are presented. Results of experimental investigation carried out by solving the competitive facility location problem using up to 2048 processing units are presented and discussed.
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Lančinskas, A., Żilinskas, J. (2013). Solution of Multi-Objective Competitive Facility Location Problems Using Parallel NSGA-II on Large Scale Computing Systems. In: Manninen, P., Öster, P. (eds) Applied Parallel and Scientific Computing. PARA 2012. Lecture Notes in Computer Science, vol 7782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36803-5_31
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DOI: https://doi.org/10.1007/978-3-642-36803-5_31
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